SoroushVahidi/scidocs huggingface dataset:
Detecting hot topics from Twitter: A multiview approach
(2014)

Twitter is widely used all over the world, and a huge number of hot topics are generated by Twitter users in real time. These topics are able to reflect almost every aspect of people’s daily lives. Therefore, the detection of topics in Twitter can be used in many real applications, such as monitoring public opinion, hot product recommendation and incidence detection. However, the performance of traditional topic detection methods is still far from perfect largely owing to the tweets’ features, such as their limited length and arbitrary abbreviations. To address these problems, we propose a novel framework (MVTD) for Twitter topic detection using multiview clustering, which can integrate multirelations among tweets, such as semantic relations, social tag relations and temporal relations. We also propose some methods for measuring relations among tweets. In particular, to better measure the semantic similarity of tweets, we propose a new document similarity measure based on a suffix tree (STVSM). In addition, a new keyword extraction method based on a suffix tree is proposed. Experiments on real datasets show that the performance of MVTD is much better than that of a single view, and it is useful for detecting topics from Twitter.
Job insecurity and organizational citizenship behavior: exploring curvilinear and moderated relationships.
(2015)

This article examined a curvilinear relationship between job insecurity and organizational citizenship behavior (OCB). Drawing from social exchange theory and research on personal control, we developed and tested an explanation for employees' reactions to job insecurity based on their conceptualization of their social exchange relationship with the organization at different levels of job insecurity. Using data from 244 Chinese employees and 102 supervisory ratings of OCB, we found support for a U-shaped relationship between job insecurity and OCB. Moreover, 2 factors--psychological capital and subordinate-supervisor guanxi--moderated the curvilinear relationship, such that the curvilinear relationship is more pronounced among those with lower psychological capital or less positive subordinate-supervisor guanxi.
A study on the road accidents using data investigation and visualization in Los Baños, Laguna, Philippines
(2018)

Road safety is one of the most vital and crucial part of every countries daily economic growth. It gives so much impact in public health specially in the Philippines. Securing its safety will be a big help to a particular country's economic growth. The main objective of this paper is to analyze road accident's data to discover hidden pattern that can be used as precautionary measure to at least lessen the accident that occur yearly in Los Baños, Laguna, Philippines. Predicting algorithms such as Decision Tree, Naïve Bayes and Rule induction were used to identify factors affecting accident in Los Baños, Laguna. Using these three classifier the following are the results obtained by the researchers; for Decision Tree 92.84% accuracy occurred with 0.797 kappa while in Naïve Bayes 91.50% accuracy was generated with 0.741 kappa and 92.50% accuracy for Rule Induction and 0.783 kappa was produced. The researchers discovered that the place where an accident happened don't have significant correlation on the fatality of the victim. On the other hand, the researchers also found that the time and day play a vital role on the fatality or severity of victims of road accident particularly car collision.
Feature reduction and selection for EMG signal classification
(2012)

0957-4174/$ see front matter 2012 Elsevier Ltd. A doi:10.1016/j.eswa.2012.01.102 ⇑ Corresponding author. Tel.: +66 74 55 8831; fax: E-mail address: angkoon.p@hotmail.com (A. Phiny Feature extraction is a significant method to extract the useful information which is hidden in surface electromyography (EMG) signal and to remove the unwanted part and interferences. To be successful in classification of the EMG signal, selection of a feature vector ought to be carefully considered. However, numerous studies of the EMG signal classification have used a feature set that have contained a number of redundant features. In this study, most complete and up-to-date thirty-seven time domain and frequency domain features have been proposed to be studied their properties. The results, which were verified by scatter plot of features, statistical analysis and classifier, indicated that most time domain features are superfluity and redundancy. They can be grouped according to mathematical property and information into four main types: energy and complexity, frequency, prediction model, and time-dependence. On the other hand, all frequency domain features are calculated based on statistical parameters of EMG power spectral density. Its performance in class separability viewpoint is not suitable for EMG recognition system. Recommendation of features to avoid the usage of redundant features for classifier in EMG signal classification applications is also proposed in this study. 2012 Elsevier Ltd. All rights reserved.
Semantic exploitation of implicit patent information
(2016)

In recent years patents have become increasingly important for businesses to protect their intellectual capital and as a valuable source of information. Patent information is, however, not employed to its full potential and the interpretation of structured and unstructured patent information in large volumes remains a challenge. We address this by proposing an integrated interdisciplinary approach that uses natural language processing and machine learning techniques to formalize multilingual patent information in an ontology. The ontology further contains patent and domain specific knowledge, which allows for aligning patents with technological fields of interest and other business-related artifacts. Our empirical evaluation shows that for categorizing patents according to well-known technological fields of interest, the approach achieves high accuracy with selected feature sets compared to related work focussing on monolingual patents. We further show that combining OWL RL reasoning with SPARQL querying over the patent knowledge base allows for answering complex business queries and illustrate this with real-world use cases from the automotive domain.
Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach
(2018)

In spatial crowdsourcing, requesters submit their task-related locations and increase the demand of a local area. The platform prices these tasks and assigns spatial workers to serve if the prices are accepted by requesters. There exist mature pricing strategies which specialize in tackling the imbalance between supply and demand in a local market. However, in global optimization, the platform should consider the mobility of workers; that is, any single worker can be the potential supply for several areas, while it can only be the true supply of one area when assigned by the platform. The hardness lies in the uncertainty of the true supply of each area, hence the existing pricing strategies do not work. In the paper, we formally define this <u>G</u>lobal <u>D</u>ynamic <u>P</u>ricing(GDP) problem in spatial crowdsourcing. And since the objective is concerned with how the platform matches the supply to areas, we let the matching algorithm guide us how to price. We propose a <u>MA</u>tching-based <u>P</u>ricing <u>S</u>trategy (MAPS) with guaranteed bound. Extensive experiments conducted on the synthetic and real datasets demonstrate the effectiveness of MAPS.
Mechanics and energetics of human locomotion on sand.
(1998)

Moving about in nature often involves walking or running on a soft yielding substratum such as sand, which has a profound effect on the mechanics and energetics of locomotion. Force platform and cinematographic analyses were used to determine the mechanical work performed by human subjects during walking and running on sand and on a hard surface. Oxygen consumption was used to determine the energetic cost of walking and running under the same conditions. Walking on sand requires 1.6-2.5 times more mechanical work than does walking on a hard surface at the same speed. In contrast, running on sand requires only 1.15 times more mechanical work than does running on a hard surface at the same speed. Walking on sand requires 2.1-2.7 times more energy expenditure than does walking on a hard surface at the same speed; while running on sand requires 1.6 times more energy expenditure than does running on a hard surface. The increase in energy cost is due primarily to two effects: the mechanical work done on the sand, and a decrease in the efficiency of positive work done by the muscles and tendons.
Open Set Learning with Counterfactual Images
(2018)

In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, we introduce a dataset augmentation technique that we call counterfactual image generation. Our approach, based on generative adversarial networks, generates examples that are close to training set examples yet do not belong to any training category. By augmenting training with examples generated by this optimization, we can reformulate open set recognition as classification with one additional class, which includes the set of novel and unknown examples. Our approach outperforms existing open set recognition algorithms on a selection of image classification tasks.
Obstacle Detection on Railway Track by Fusing Radar and Image Sensor
(2011)

Novel technology to recognize the situation in distant place is necessary to develop a railway safety monitoring system by which human being having fallen onto the tracks from a platform and obstacles in the level crossing can be detected. In this research, we propose a method for detecting a stationary or moving obstacle by the technology which employs the super resolution radar techniques, the image recognition techniques, and the technology to fuse these techniques. Our method is designed for detecting obstacles such as cars, bicycles, and human on the track in the range up to hundreds of meters ahead by using sensors mounted on a train. In super resolution radar techniques, novel stepped multiple frequency radar is confirmed to provide the expected high resolution performance by experimental study using software defined radar. We designed the parameters of the stepped multiple frequency radar. The signal processing processor which employs A/Ds, D/As of high-sampling rate and the highest performance FPGAs has been designed and developed. In image recognition techniques, the main algorithm which detects a pair of rails is based on information about rail edges and intensity gradients. As the obstacle exists in the vicinity of rails, all the detection processes can be limited to the region in the vicinity of rails. As an example, we detect an obstacle by estimating image boundaries which enclose a group of feature points exactly on the obstacle. In order to determine the group of feature points, feature points of the whole image are detected at each frames and tracked over image sequence. For robustness estimation of boundary, we use radar so as to detect the obstacle’s rough position in an image region where an obstacle would exist; the motion segmentation technique is applied to the tracks that is located in the region. Note that an obstacle's position detected by radar is remarkably rough because radar has low transverse resolution. Nevertheless, the position detected by radar contributes to rapid and robust estimation of satisfactory image boundaries. To allow for monitoring in large distances, a prototype for an onboard pan/tilt camera platform with directional control was designed and manufactured as required in a railway situation. To detect obstacles in real time, we have built a high-performance test machine with a GPU and an image processing environment.
The potential distribution measurement on the stress grading system of high-voltage rotating machines by using pockels effect
(2012)

A surface potential measuring system was developed by utilizing Pockels sensor for measuring the potential distribution on the stress grading (SG) system of form wound motor coils. A Bi4Ge3O12 (BGO) Pockels crystal is put close to a measuring object and the capacitively-induced voltage on the end surface of the BGO crystal is measured by using Pockels effect of the crystal itself. The spatial resolution of the measuring system is 5 mm, and the frequency response reaches up to GHz-range. With this system, the surface potential distributions on a model bar coil were measured. According to the measuring results, it is shown that the newly developed potential measuring system here is very useful for evaluating the reliability of the SG system of motors.
Polarization-agile antennas
(2006)

A polarization-agile antenna is a type of antenna the polarization state of which can be changed dynamically, i.e., it can have either linear (vertical or horizontal) or circular polarization (left hand or right hand), depending on the requirements of its specific application. This special characteristic offers great flexibility for antenna systems, because a single antenna could be used to satisfy the different requirements of several systems. This paper gives a comprehensive review of polarization-agile antennas. The basics of polarization in antennas and polarization-agile antennas are explained. Various examples of recent developments are then provided, and the antenna configurations and design principles are illustrated and discussed. Finally, the future development of polarization-agile antennas for wireless systems is discussed
A Method for the Analytical Extraction of the Single-Diode PV Model Parameters
(2016)

Determination of PV model parameters usually requires time consuming iterative procedures, prone to initialization and convergence difficulties. In this paper, a set of analytical expressions is introduced to determine the five parameters of the single-diode model for crystalline PV modules at any operating conditions, in a simple and straightforward manner. The derivation of these equations is based on a newly found relation between the diode ideality factor and the open circuit voltage, which is explicitly formulated using the temperature coefficients. The proposed extraction method is robust, cost-efficient, and easy-to-implement, as it relies only on datasheet information, while it is based on a solid theoretical background. Its accuracy and computational efficiency is verified and compared to other methods available in the literature through both simulation and outdoor measurements.
Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays
(2009)

This paper proposes a method of modeling and simulation of photovoltaic arrays. The main objective is to find the parameters of the nonlinear I-V equation by adjusting the curve at three points: open circuit, maximum power, and short circuit. Given these three points, which are provided by all commercial array data sheets, the method finds the best I-V equation for the single-diode photovoltaic (PV) model including the effect of the series and parallel resistances, and warranties that the maximum power of the model matches with the maximum power of the real array. With the parameters of the adjusted I-V equation, one can build a PV circuit model with any circuit simulator by using basic math blocks. The modeling method and the proposed circuit model are useful for power electronics designers who need a simple, fast, accurate, and easy-to-use modeling method for using in simulations of PV systems. In the first pages, the reader will find a tutorial on PV devices and will understand the parameters that compose the single-diode PV model. The modeling method is then introduced and presented in details. The model is validated with experimental data of commercial PV arrays.
Identification of Photovoltaic Source Models
(2011)

This paper presents a photovoltaic (PV) model estimation method from the PV module data. The model is based on a single-diode model of a PV cell. The cell model of a module is extended to estimate the parameters of arrays. The variation of the parameters with change in temperature and irradiance is also studied. Finally, estimation of the maximum power point from the estimated parameters under varying environmental conditions is presented.
On the Parameter Extraction of a Five-Parameter Double-Diode Model of Photovoltaic Cells and Modules
(2014)

The main contribution of this paper is to present a new set of approximate analytical solutions for the parameters of a photovoltaic (PV) five-parameter double-diode model that can be used as initial values for the numerical solutions based on the Newton-Raphson method. The proposed formulations are developed based on only the limited information given by the PV manufacturers, i.e., the open-circuit voltage ( Voc), the short circuit current ( Isc), and the current and voltage at the maximum power point (Im and Vm). Compared with the existing techniques that require the entire experimental I-V curve or additional information such as the slope of the I-V curves of the open circuit and the short circuit points, the proposed technique is quite independent of these additional data, and, it is therefore, a low cost and fast parameter extraction method. The accuracy of the theoretical I-V curves is evaluated through the comparison of the simulation results and experimental data. The results of the application of the proposed technique to different PV modules show the accuracy and validity of the proposed analytical-numerical method.
PV panel model based on datasheet values
(2007)

This work presents the construction of a model for a PV panel using the single-diode five-parameters model, based exclusively on data-sheet parameters. The model takes into account the series and parallel (shunt) resistance of the panel. The equivalent circuit and the basic equations of the PV cell/panel in Standard Test Conditions (STC)1 are shown, as well as the parameters extraction from the data-sheet values. The temperature dependence of the cell dark saturation current is expressed with an alternative formula, which gives better correlation with the datasheet values of the power temperature dependence. Based on these equations, a PV panel model, which is able to predict the panel behavior in different temperature and irradiance conditions, is built and tested.
A Practical Method for Modeling PCB Transmission Lines with Conductor Surface Roughness and Wideband Dielectric Properties
(2006)

This paper discusses the modeling techniques to account for transmission line high frequency effects, and proposes a method to integrate these techniques into a practical and design-worthy model generation flow. The frequency tabulated transmission line models are capable of predicting wideband dielectric characteristics and high frequency conductor losses due to skin effect and surface roughness. They can be used to accurately model high volume, low cost printed circuit board traces which often have roughened trace surfaces and pronounced frequency variation in dielectric properties. The model accuracy is verified up to 20 GHz in frequency domain, thus suitable for multi-gigabit signaling analysis
Moving Right Along: A Computational Model of Metaphoric Reasoning about Events
(1999)

This paper describes the results of an implemented computational model that cashes out the belief that metaphor interpretation is grounded in embodied primitives. The speci c task addressed is the interpretation of simple causal narratives in the domains of Politics and Economics. The stories are taken from newspaper articles in these domains. When presented with a preparsed version of these narratives as input, the system described is able to generate commonsense inferences consistent with the input.
A service-oriented mobile augmented reality architecture for personalized museum environments
(2014)

This paper presents a mobile augmented reality platform that exploits service-orientation for the visualisation of cultural media objects in personalised interactive museum environments. The service orientated architecture is composed of a mobile client, web service framework and service providers utilized to perform augmented reality tasks as well as support for media contents acquisition and consumption via a mobile or wireless network. The mobile client performs augmented reality tasks including multiple object tracking of physical 3D objects concurrently and then visualizes associated media contents (e.g. 3D models, videos, images, text, social media data, etc.) that are associated with the tracked physical (or reference) objects and then overlaid in the correct perspective in the real scene in a personalised museum visualisation scenario. A unique feature includes media content acquisition from open service providers through a web service framework. Typical services include, a photogrammetry service that allows users to obtain virtual 3D models of preferred cultural objects through image-based reconstruction techniques. These acquired 3D reconstruction contents can then be integrated with existing associated contents in a personalized augmented reality museum environment that can be stored and saved for later viewing, such as in the home after visiting a particular augmented reality based museum interactive. This paper focuses on describing the service orientation architectural components that supports personalized mobile augmented reality museum environments.
Firefly Algorithm for Continuous Constrained Optimization Tasks
(2009)

The paper provides an insight into the improved novel metaheuristics of the Firefly Algorithm for constrained continuous optimization tasks. The presented technique is inspired by social behavior of fireflies and the phenomenon of bioluminescent communication. The first part of the paper is devoted to the detailed description of the existing algorithm. Then some suggestions for extending the simple scheme of the technique under consideration are presented. Subsequent sections concentrate on the performed experimental parameter studies and a comparison with existing Particle Swarm Optimization strategy based on existing benchmark instances. Finally some concluding remarks on possible algorithm extensions are given, as well as some properties of the presented approach and comments on its performance in the constrained continuous optimization tasks.